Skip to main content

Table 2 Overview of core pharmacokinetic analytical methods [67]

From: Pharmacokinetic–Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance

Method Description Comments
Naive pooled data approach All PK data from the study are pooled and analyzed as if from one individual The analysis does not incorporate the fact that the data arise from individuals with between-subject variability, and can give biased parameter estimates; it can be used in unbalanced study designs but will overestimate variability and can lead to biased parameter estimates
Naive average data approach The mean drug concentration at each time point in the PK study is calculated, based on the data at that time point contributed by all participants. The mean value at each sampling time is then used to estimate the PK parameters of interest This simplistic approach is popular but is unreliable and limited because it does not consider inter- or intraindividual variability, and therefore underestimates variability. It is only suitable for a balanced study design
Two-stage approach The PK parameters are first estimated for each individual, then the variance of these parameter estimates is calculated This method is attractive because it is mathematically straightforward, but requires rich individual-level data
Non-linear mixed effect modeling (NLME) All study data are fitted simultaneously in one model, but the PK parameters are able to vary between individuals This approach has become standard practice because it provides unbiased parameter estimates through simultaneous quantification of parameter-level interindividual variability, and observation-level residual variability
  1. PK pharmacokinetic